Sql what makes a good index

That is the clustered index that was referenced earlier in the article that is automatically created based off of the primary key. That index was created similarly to the names index:. This provides a way for our database to swiftly query city names. After your non-clustered indexes are created you can begin querying with them. Indexes use an optimal search method known as binary search. Binary searches work by constantly cutting the data in half and checking if the entry you are searching for comes before or after the entry in the middle of the current portion of data.

This works well with B-trees because they are designed to start at the middle entry; to search for the entries within the tree you know the entries down the left path will be smaller or before the current entry and the entries to the right will be larger or after the current entry.

In a table this would look like:. Comparing this method to the query of the non-indexed table at the beginning of the article, we are able to reduce the total number of searches from eight to three.

Using this method, a search of 1,, entries can be reduced down to just 20 jumps in a binary search. Indexes are meant to speed up the performance of a database, so use indexing whenever it significantly improves the performance of your database. As your database becomes larger and larger, the more likely you are to see benefits from indexing. When data is written to the database, the original table the clustered index is updated first and then all of the indexes off of that table are updated.

Every time a write is made to the database, the indexes are unusable until they have updated. If the database is constantly receiving writes then the indexes will never be usable. This is why indexes are typically applied to databases in data warehouses that get new data updated on a scheduled basis off-peak hours and not production databases which might be receiving new writes all the time. NOTE: The newest version of Postgres that is currently in beta will allow you to query the database while the indexes are being updated.

To test if indexes will begin to decrease query times, you can run a set of queries on your database, record the time it takes those queries to finish, and then begin creating indexes and rerunning your tests.

This output will tell you which method of search from the query plan was chosen and how long the planning and execution of the query took. What is Indexing? It is interesting that SQL Server did not recognize that there is already a covering clustered index and use that one.

Before we added the primary key constraint, it was possible and permissible to add new customers with the same customer IDs as existing customers. Go ahead, try it! Now that the PK is in place, though, that is no longer possible. Although there can be only one primary key, there can be other keys, if other combinations of columns are truly unique. Creating them uses similar syntax:.

Primary keys are necessary to make a table conform to relational theory. In practice, they are highly useful as are unique keys for referential integrity and a good way to get the database to check your assumptions about incoming data. By default, SQL Server creates a clustered index when you create a new table with a primary key:.

While a primary key needs to be backed by an index to implement the constraint, the index does not need to be clustered, as we saw above. Furthermore, the goals of primary keys and clustered indexes may not be the same. Fundamentally, a primary key constraint enables SQL Server to maintain the important property that a table may not have duplicate rows. In fact, unique constraints do exactly the same thing.

Because they are backed by indexes, keys are also helpful for searches, since. On the other hand, clustered indexes can provide a performance advantage when reading the table in index order. This allows SQL Server to better use read ahead reads, which are asymptotically faster than page-by-page reads.

Also, a clustered index does not require uniqueness. If two or more rows have the same clustered index key, a uniqueifier is added to ensure that all rows in the index are unique.

The point here is to carefully consider which arrangement is best for a new table. Consult with business users about how the table will be used. Remember that most reporting is sequential in nature. Choose your indexing accordingly, then test it. Use real workloads and see if actual usage is still a good match for the indexing scheme. If not, adjust it to suit. Sometimes, a message will be included with the execution plan that an index is missing.

For example, if I remove the indexes from the Customer table and try a search by CustomerID, the resulting plan looks like this:. The text in green, above, is just such a message. Basically, SQL Server is saying that if there were an index on the CustomerID column, the cost of the overall query could be reduced by That would reduce the cost to almost nothing. Instead of a table scan, it could use an index seek operation.

The question then becomes, should you always implement a missing index? Is this a once-a-year query that runs in 10 minutes without the index?

Perhaps you can leave that missing index alone. Is it a query that gets executed thousands of times a second from a busy e-commerce server? Probably you should implement the recommendation! You need to think it through and understand the usage patterns and the cost of an index before you do anything. Come to think about it…. There is actually advice out in the wild stating that you should just index every column in your table so that no execution plan will ever have a missing index.

Is this good advice? Once again, it depends. Data warehouse databases often have a calendar table. Such a table is static. Often the primary key and clustered index is an integer or date column with the date matching the other columns in the row. This table never or rarely changes. Also, it is not too big. How many rows would you need for a century? On such a table, indexing every column can make sense. You can have filtered indexes for the various flags, ascending and descending indexes, most of which will be nonclustered.

Now consider our Customer table. If we index every column, what happens when we insert a new customer? All those indexes must be maintained! This work can add up quickly, so unless you have a static table such as a calendar table , indexing every column is usually a bad idea!

Properly indexing a SQL Server table is key to providing consistent, optimal performance. There are many things to consider when designing an index structure. Almost none of those considerations can be done without consulting the business users who understand the data and how it will be used, though it may well turn out that, after the new table has been in use for some time, that other indexing options will present themselves.

This article has attempted to answer some of the most important questions about indexing in general and specifically how it is done in SQL Server. Each question answered here could be its own complete article and possibly a series of articles! XML indexes nor have we looked at in-memory objects and how those change the picture for newer editions of SQL Server. SUM a. AND t. AND i. When a column is updated, all indexes on the column must be updated.

You must weigh the performance benefit of indexes for queries against the performance overhead of updates. For example, if a table is primarily read-only, you might use more indexes; but, if a table is heavily updated, you might use fewer indexes.

In general, you should put the column expected to be used most often first in the index. You can create a composite index using several columns , and the same index can be used for queries that reference all of these columns, or just some of them. To increase the performance of such queries, you might create a composite index putting the most selective column first; that is, the column with the most values:.

Composite indexes speed up queries that use the leading portion of the index. The database can use indexes more effectively when it has statistical information about the tables involved in the queries. When you drop an index, all extents of the index's segment are returned to the containing tablespace and become available for other objects in the tablespace. For example, the following statement drops a specific named index:.

When using indexes in an application, you might need to request that the DBA grant privileges or make changes to initialization parameters. To create a new index, you must own, or have the INDEX object privilege for, the corresponding table. You can create an index for a table to improve the performance of queries issued against the corresponding table. You can also create an index for a cluster. You can create a composite index on multiple columns up to a maximum of 32 columns.

A composite index key cannot exceed roughly one-half minus some overhead of the available space in the data block. In this example, an index is created for a single column, to speed up queries that test that column:.

In this example, the index applies to two columns, to speed up queries that test either the first column or both columns:. An index on the ENAME column itself would not speed up this operation, and it might be slow to call the function for each result row.

A function-based index precomputes the result of the function for each column value, speeding up queries that use the function for searching or sorting:. Domain indexes are appropriate for special-purpose applications implemented using data cartridges. The domain index helps to manipulate complex data, such as spatial, audio, or video data.

Oracle Database supplies a number of specialized data cartridges to help manage these kinds of complex data. So, if you need to create a search engine, or a geographic information system, you can do much of the work simply by creating the right kind of index.